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Commit 201eaf53 authored by chenych's avatar chenych
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update test

parent 388cb6a5
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Showing with 15 additions and 12 deletions
main.py
View file @ 201eaf53
...@@ -80,7 +80,7 @@ def get_args_parser(): ...@@ -80,7 +80,7 @@ def get_args_parser():
# dataset parameters # dataset parameters
parser.add_argument('--dataset_file', default='coco') parser.add_argument('--dataset_file', default='coco')
parser.add_argument('--coco_path', default='../datasets/COCO2017', type=str) parser.add_argument('--coco_path', default='/home/datasets/COCO2017', type=str)
parser.add_argument('--coco_panoptic_path', type=str) parser.add_argument('--coco_panoptic_path', type=str)
parser.add_argument('--remove_difficult', action='store_true') parser.add_argument('--remove_difficult', action='store_true')
......
results-1201/log.txt 0 → 100644
View file @ 201eaf53
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{"train_lr": 9.99999999999901e-05, "train_class_error": 75.29489056331677, "train_loss": 18.381440653621013, "train_loss_bbox": 0.723692496479904, "train_loss_bbox_0": 0.8269315716677874, "train_loss_bbox_1": 0.7672487141076467, "train_loss_bbox_2": 0.7405738953859254, "train_loss_bbox_3": 0.7255249568086732, "train_loss_bbox_4": 0.7214213650954296, "train_loss_ce": 1.0465436161761676, "train_loss_ce_0": 1.1402332862078475, "train_loss_ce_1": 1.08618309340457, "train_loss_ce_2": 1.0699610818380532, "train_loss_ce_3": 1.057397855381496, "train_loss_ce_4": 1.0498246611853697, "train_loss_giou": 1.212658500173136, "train_loss_giou_0": 1.306608321015928, "train_loss_giou_1": 1.2521192761641724, "train_loss_giou_2": 1.2291900435820107, "train_loss_giou_3": 1.2145628486456994, "train_loss_giou_4": 1.2107650697126482, "train_cardinality_error_unscaled": 9.71369876910591, "train_cardinality_error_0_unscaled": 8.571714797781686, "train_cardinality_error_1_unscaled": 8.880748681184905, "train_cardinality_error_2_unscaled": 9.141595089949952, "train_cardinality_error_3_unscaled": 9.333719396726634, "train_cardinality_error_4_unscaled": 9.532953469498175, "train_class_error_unscaled": 75.29489056331677, "train_loss_bbox_unscaled": 0.14473849933669544, "train_loss_bbox_0_unscaled": 0.16538631436288415, "train_loss_bbox_1_unscaled": 0.1534497428397703, "train_loss_bbox_2_unscaled": 0.1481147790457421, "train_loss_bbox_3_unscaled": 0.14510499137715382, "train_loss_bbox_4_unscaled": 0.1442842730282568, "train_loss_ce_unscaled": 1.0465436161761676, "train_loss_ce_0_unscaled": 1.1402332862078475, "train_loss_ce_1_unscaled": 1.08618309340457, "train_loss_ce_2_unscaled": 1.0699610818380532, "train_loss_ce_3_unscaled": 1.057397855381496, "train_loss_ce_4_unscaled": 1.0498246611853697, "train_loss_giou_unscaled": 0.606329250086568, "train_loss_giou_0_unscaled": 0.653304160507964, "train_loss_giou_1_unscaled": 0.6260596380820862, "train_loss_giou_2_unscaled": 0.6145950217910053, "train_loss_giou_3_unscaled": 0.6072814243228497, "train_loss_giou_4_unscaled": 0.6053825348563241, "test_class_error": 71.37280010986328, "test_loss": 16.858334786987303, "test_loss_bbox": 0.6054652205944061, "test_loss_bbox_0": 0.6731032344341278, "test_loss_bbox_1": 0.6374604082107544, "test_loss_bbox_2": 0.6178004308223725, "test_loss_bbox_3": 0.6174909641265869, "test_loss_bbox_4": 0.6099482417583466, "test_loss_ce": 0.9717377951145172, "test_loss_ce_0": 1.028515016269684, "test_loss_ce_1": 0.9978056359767914, "test_loss_ce_2": 0.9846026960372924, "test_loss_ce_3": 0.976672312784195, "test_loss_ce_4": 0.9680032284259796, "test_loss_giou": 1.1705320921897888, "test_loss_giou_0": 1.2570975029945373, "test_loss_giou_1": 1.203470858001709, "test_loss_giou_2": 1.1817519565582275, "test_loss_giou_3": 1.19222730884552, "test_loss_giou_4": 1.1646499029159545, "test_cardinality_error_unscaled": 10.0948, "test_cardinality_error_0_unscaled": 9.6092, "test_cardinality_error_1_unscaled": 9.236, "test_cardinality_error_2_unscaled": 9.9606, "test_cardinality_error_3_unscaled": 10.6488, "test_cardinality_error_4_unscaled": 10.2552, "test_class_error_unscaled": 71.37280010986328, "test_loss_bbox_unscaled": 0.121093044090271, "test_loss_bbox_0_unscaled": 0.13462064687013625, "test_loss_bbox_1_unscaled": 0.12749208160638809, "test_loss_bbox_2_unscaled": 0.12356008599996567, "test_loss_bbox_3_unscaled": 0.1234981928229332, "test_loss_bbox_4_unscaled": 0.12198964867591858, "test_loss_ce_unscaled": 0.9717377951145172, "test_loss_ce_0_unscaled": 1.028515016269684, "test_loss_ce_1_unscaled": 0.9978056359767914, "test_loss_ce_2_unscaled": 0.9846026960372924, "test_loss_ce_3_unscaled": 0.976672312784195, "test_loss_ce_4_unscaled": 0.9680032284259796, "test_loss_giou_unscaled": 0.5852660460948944, "test_loss_giou_0_unscaled": 0.6285487514972686, "test_loss_giou_1_unscaled": 0.6017354290008545, "test_loss_giou_2_unscaled": 0.5908759782791138, "test_loss_giou_3_unscaled": 0.59611365442276, "test_loss_giou_4_unscaled": 0.5823249514579772, "test_coco_eval_bbox": [0.01955836267782286, 0.05595620142946556, 0.010218387349830584, 0.006430131119293399, 0.01915705634248169, 0.034795495582876396, 0.055137544801095145, 0.12620218155803534, 0.16582232911906114, 0.016133826104210422, 0.12634812013609983, 0.3259466540608769], "epoch": 1, "n_parameters": 41302368}
{"train_lr": 9.99999999999901e-05, "train_class_error": 65.83424340548284, "train_loss": 15.985444009376607, "train_loss_bbox": 0.5973874089759951, "train_loss_bbox_0": 0.6726899858875042, "train_loss_bbox_1": 0.6427748496947165, "train_loss_bbox_2": 0.6187591244008437, "train_loss_bbox_3": 0.6034305870077469, "train_loss_bbox_4": 0.5977342998898434, "train_loss_ce": 0.9084787015262353, "train_loss_ce_0": 0.9662109515743715, "train_loss_ce_1": 0.9379078723952813, "train_loss_ce_2": 0.9251700814273704, "train_loss_ce_3": 0.9156807647572308, "train_loss_ce_4": 0.9100717926672794, "train_loss_giou": 1.0890286348374145, "train_loss_giou_0": 1.1656269748043533, "train_loss_giou_1": 1.135923827603917, "train_loss_giou_2": 1.1124295851954682, "train_loss_giou_3": 1.0959127130389745, "train_loss_giou_4": 1.0902258645439284, "train_cardinality_error_unscaled": 11.234267212227783, "train_cardinality_error_0_unscaled": 10.051239348031922, "train_cardinality_error_1_unscaled": 10.377214933044772, "train_cardinality_error_2_unscaled": 10.679620925199513, "train_cardinality_error_3_unscaled": 10.847068172595698, "train_cardinality_error_4_unscaled": 11.052947044501556, "train_class_error_unscaled": 65.83424340548284, "train_loss_bbox_unscaled": 0.11947748173180911, "train_loss_bbox_0_unscaled": 0.1345379971976566, "train_loss_bbox_1_unscaled": 0.1285549700071202, "train_loss_bbox_2_unscaled": 0.12375182490536345, "train_loss_bbox_3_unscaled": 0.12068611742714722, "train_loss_bbox_4_unscaled": 0.11954685994299842, "train_loss_ce_unscaled": 0.9084787015262353, "train_loss_ce_0_unscaled": 0.9662109515743715, "train_loss_ce_1_unscaled": 0.9379078723952813, "train_loss_ce_2_unscaled": 0.9251700814273704, "train_loss_ce_3_unscaled": 0.9156807647572308, "train_loss_ce_4_unscaled": 0.9100717926672794, "train_loss_giou_unscaled": 0.5445143174187073, "train_loss_giou_0_unscaled": 0.5828134874021766, "train_loss_giou_1_unscaled": 0.5679619138019585, "train_loss_giou_2_unscaled": 0.5562147925977341, "train_loss_giou_3_unscaled": 0.5479563565194873, "train_loss_giou_4_unscaled": 0.5451129322719642, "test_class_error": 56.81704413146973, "test_loss": 15.200364082336426, "test_loss_bbox": 0.5247525475978851, "test_loss_bbox_0": 0.5932301633834839, "test_loss_bbox_1": 0.560852001285553, "test_loss_bbox_2": 0.5421994529724121, "test_loss_bbox_3": 0.522824534034729, "test_loss_bbox_4": 0.5207232820034027, "test_loss_ce": 0.8807210395336151, "test_loss_ce_0": 0.9172440742969513, "test_loss_ce_1": 0.9003739905357361, "test_loss_ce_2": 0.8944099536895752, "test_loss_ce_3": 0.8844890825748444, "test_loss_ce_4": 0.8803118057727813, "test_loss_giou": 1.058423937177658, "test_loss_giou_0": 1.1634227115631104, "test_loss_giou_1": 1.11607975358963, "test_loss_giou_2": 1.1074692643642425, "test_loss_giou_3": 1.0670125399112702, "test_loss_giou_4": 1.0658239573478698, "test_cardinality_error_unscaled": 15.3628, "test_cardinality_error_0_unscaled": 16.4986, "test_cardinality_error_1_unscaled": 16.79, "test_cardinality_error_2_unscaled": 16.7054, "test_cardinality_error_3_unscaled": 15.5102, "test_cardinality_error_4_unscaled": 15.0888, "test_class_error_unscaled": 56.81704413146973, "test_loss_bbox_unscaled": 0.10495050947666168, "test_loss_bbox_0_unscaled": 0.11864603291749955, "test_loss_bbox_1_unscaled": 0.11217040014266967, "test_loss_bbox_2_unscaled": 0.10843989049196243, "test_loss_bbox_3_unscaled": 0.10456490672826767, "test_loss_bbox_4_unscaled": 0.10414465627670288, "test_loss_ce_unscaled": 0.8807210395336151, "test_loss_ce_0_unscaled": 0.9172440742969513, "test_loss_ce_1_unscaled": 0.9003739905357361, "test_loss_ce_2_unscaled": 0.8944099536895752, "test_loss_ce_3_unscaled": 0.8844890825748444, "test_loss_ce_4_unscaled": 0.8803118057727813, "test_loss_giou_unscaled": 0.529211968588829, "test_loss_giou_0_unscaled": 0.5817113557815552, "test_loss_giou_1_unscaled": 0.558039876794815, "test_loss_giou_2_unscaled": 0.5537346321821213, "test_loss_giou_3_unscaled": 0.5335062699556351, "test_loss_giou_4_unscaled": 0.5329119786739349, "test_coco_eval_bbox": [0.03485322822674695, 0.08978358956699144, 0.022399539171381076, 0.009762919976685899, 0.036354291754086616, 0.056886859335906315, 0.08385506834103959, 0.18074649934381484, 0.22781578570560013, 0.029978428118976917, 0.20357599381602318, 0.4221100385012155], "epoch": 2, "n_parameters": 41302368}
test.py
View file @ 201eaf53
...@@ -77,14 +77,15 @@ def test_img(args, model, postprocessors, save_path): ...@@ -77,14 +77,15 @@ def test_img(args, model, postprocessors, save_path):
def get_parser(): def get_parser():
parser = argparse.ArgumentParser("DETR Detector", add_help=False) parser = argparse.ArgumentParser("DETR Detector", add_help=False)
parser.add_argument('--dataset_file', default='coco') parser.add_argument('--dataset_file', default='coco')
parser.add_argument('--coco_path', default='../datasets/COCO2017', type=str) parser.add_argument('--coco_path', default='/home/datasets/COCO2017', type=str)
parser.add_argument('--coco_panoptic_path', type=str) parser.add_argument('--coco_panoptic_path', type=str)
parser.add_argument('--remove_difficult', action='store_true') parser.add_argument('--remove_difficult', action='store_true')
parser.add_argument("--save_path", default="./result_img", type=str)
parser.add_argument('--output_dir', default='', parser.add_argument('--output_dir', default='',
help='path where to save, empty for no saving') help='path where to save, empty for no saving')
parser.add_argument('--device', default='cuda:0', parser.add_argument('--device', default='cuda',
help='device to use for training / testing') help='device to use for training / testing')
parser.add_argument("--pre_trained_model", default="")
parser.add_argument('--seed', default=42, type=int) parser.add_argument('--seed', default=42, type=int)
# * Segmentation # * Segmentation
parser.add_argument('--masks', action='store_true', parser.add_argument('--masks', action='store_true',
...@@ -130,16 +131,14 @@ if __name__ == "__main__": ...@@ -130,16 +131,14 @@ if __name__ == "__main__":
args = get_parser().parse_args() args = get_parser().parse_args()
device = torch.device(args.device) device = torch.device(args.device)
load_path = './checkpoints/r50_hybrid_branch_lambda1_group6_t1500_dp0_mqs_lft_deformable_detr_plus_iterative_bbox_refinement_plus_plus_two_stage_36eps.pth' if not os.path.exists(args.save_path):
img_path = '/home/datasets/COCO2017' os.makedirs()
save_path = './result'
if not os.path.exists(save_path):
os.makedirs(save_path)
model, postprocessors = build_test_model(args) model, postprocessors = build_test_model(args)
model.to(device) model.to(device)
checkpoint = torch.load(load_path, map_location='cpu') checkpoint = torch.load(args.pre_trained_model, map_location='cpu')
model.load_state_dict(checkpoint["model"], False) model.load_state_dict(checkpoint["model"], False)
model.eval() model.eval()
test_img(args, model, postprocessors, save_path) test_img(args, model, postprocessors, args.save_path)
val.sh
View file @ 201eaf53
...@@ -5,4 +5,5 @@ export HIP_VISIBLE_DEVICES=1 ...@@ -5,4 +5,5 @@ export HIP_VISIBLE_DEVICES=1
# resume是待测试模型地址 # resume是待测试模型地址
# coco_path是训练数据集地址，数据是coco format # coco_path是训练数据集地址，数据是coco format
# python main.py --batch_size 2 --no_aux_loss --eval --resume path/of/model --coco_path /path/to/coco # python main.py --batch_size 2 --no_aux_loss --eval --resume path/of/model --coco_path /path/to/coco
python main.py --batch_size 2 --no_aux_loss --eval --resume https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth --coco_path /home/datasets/COCO2017 # python main.py --batch_size 2 --no_aux_loss --eval --resume https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth --coco_path /home/datasets/COCO2017
python main.py --batch_size 2 --no_aux_loss --eval --resume ./results/checkpoint.pth --coco_path /home/datasets/COCO2017
\ No newline at end of file
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